Abstract
Aims
Exposure to particulate matter air pollution ≤2.5 µm (PM2.5) is associated with cardiovascular (CV) and kidney morbidity and mortality. This post hoc analysis of FIDELITY, a prespecified pooled analysis of phase 3 randomized clinical trials (FIDELIO-DKD [NCT02540993], FIGARO-DKD [NCT02545049]), determined the impact of PM2.5 exposure on CV and kidney events and the effects of finerenone on these outcomes across PM2.5 exposures in patients with CKD and T2D.
Methods
Patients with CKD and T2D on optimized renin–angiotensin system blockade were randomized 1:1 to finerenone or placebo. Key outcomes included composite CV outcomes (CV death, nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure); composite kidney outcomes (kidney failure, sustained ≥57 % decrease in eGFR, kidney-related death); combined composite CV and kidney outcomes; and safety. Outcomes were stratified by PM2.5 exposure and patients grouped into quartiles of median PM2.5 exposure with interquartile range as cutoffs.
Results
Median PM2.5 exposure was 15.5 µg/m3 (N = 12 990). Increased PM2.5 exposure was associated with higher occurrence of CV and kidney events. Finerenone reduced composite CV (hazard ratio [HR], 0.86; 95 % CI, 0.78–0.95), kidney (HR, 0.76; 95 % CI, 0.66–0.88) and combined CV and kidney (HR, 0.83; 95 % CI, 0.76–0.90) outcomes versus placebo across PM2.5 exposures (Pinteraction=0.37, 0.14, and 0.74, respectively). Proportions of adverse events (AEs) and serious AEs were generally balanced between treatment arms. Across PM2.5 quartiles, hyperkalemia was more frequent with finerenone, but few led to hospitalization.
Conclusions
Increased PM2.5 exposure is associated with higher occurrence of CV and kidney events. Finerenone lowered the risk of CV and kidney events regardless of PM2.5 exposure levels in patients with CKD and T2D.
Keywords: Air pollution, PM2.5 exposure, Chronic kidney disease, Type 2 diabetes, Finerenone
Graphical abstract
Glossary
- AE
adverse event
- BMI
body mass index
- CV
cardiovascular
- CVD
cardiovascular disease
- DPP-4
dipeptidyl peptidase-4
- eGFR
estimated glomerular filtration rate
- EOS
end of study
- FAS
full analysis set
- GLP-1RA
glucagon-like peptide-1 receptor agonist
- HbA1c
glycated hemoglobin
- HHF
hospitalization for heart failure
- hs-CRP
high-sensitivity C-reactive protein
- LS
least-squares
- NAAQS
national ambient air quality standard
- PM2.5
particulate matter with an aerodynamic diameter <2.5 µm
- PY
patient-years
- Q
quartile
- RASi
renin–angiotensin system inhibitor
- SAE
serious adverse event
- SGLT-2
sodium-glucose co-transporter-2
- T2D
type 2 diabetes
- TE
treatment-emergent
- UACR
urine albumin-to-creatinine ratio
Central illustration. Impact of ambient PM2.5 on CV and kidney events and on finerenone efficacy in individuals with CKD and T2D. Abbreviations: CKD, chronic kidney disease; CV, cardiovascular; eGFR, estimated glomerular filtration rate; HHF, hospitalization for heart failure; [K+], potassium concentration; MI, myocardial infarction; od, once daily; PM2.5, particulate matter with an aerodynamic diameter <2.5 µm; RASi, renin-angiotensin system inhibitor; T2D, type 2 diabetes. *Patients on optimized RASi blockade randomized.
1. Introduction
Air pollution is a leading environmental contributor to global cardiovascular (CV) disease (CVD) burden [1]. Particulate matter air pollution ≤2.5 µm (PM2.5) contributes substantially to this toll [2] as an independent risk factor for CVD-related morbidity and mortality [1,3,4]. PM2.5 exposure is also associated with increased risk factors for CVD including insulin resistance, type 2 diabetes (T2D), atherosclerotic CVD, and chronic kidney disease (CKD) [[5], [6], [7]]. Evidence points to the adverse effects of PM2.5 even at very low levels of air pollution [8,9].
Several science and policy guidance documents have endorsed the importance of identifying those at risk of adverse health effects of air pollution and finding measures to reduce exposure and/or mitigate risk [10,11], including preventive therapies that target pathophysiologic pathways underlying air pollution–mediated cardiometabolic risk [7]. An important question is whether common treatments confer added benefit to individuals exposed to high PM2.5 levels.
In FIDELITY, a prespecified pooled analysis of two phase 3 trials, the nonsteroidal mineralocorticoid receptor antagonist finerenone reduced the risk of CV and kidney outcomes versus placebo in patients with CKD and T2D [[12], [13], [14]]. In this post hoc analysis of FIDELITY, we examined the effects of ambient PM2.5 on CV and kidney events and the treatment effects of finerenone on PM2.5-associated CV and kidney outcomes in individuals with CKD and T2D.
2. Methods
2.1. Study design and patients
This FIDELITY analysis combined individual patient-level data from the FIDELIO-DKD (NCT02540993) and FIGARO-DKD (NCT02545049) trials. The study design, investigators, procedures, and outcomes of the FIDELITY analysis were published previously [[12], [13], [14]]. Briefly, adults (aged ≥18 years) with CKD (urine albumin-to-creatinine ratio [UACR] 30 to <300 mg/g and estimated glomerular filtration rate [eGFR] 25 to ≤90 mL/min/1.73 m2 or UACR 300 to ≤5000 mg/g and eGFR ≥25 mL/min/1.73 m2) and T2D, on optimized renin–angiotensin system blockade, were eligible to participate if they had a serum potassium level ≤4.8 mmol/L at run-in and screening and were not clinically diagnosed with symptomatic chronic heart failure with reduced ejection fraction during the run-in period.
2.2. Randomization and masking
Patients were randomly assigned (1:1) to once-daily oral finerenone (10 mg or 20 mg) or placebo. Randomization was stratified by region (North America, Europe, Asia, Latin America, or other), albuminuria at screening (moderately or severely increased), eGFR at screening (25 to <45 mL/min/1.73 m2, 45 to <60 mL/min/1.73 m2, or ≥60 mL/min/1.73 m2) and CVD history. All patients and study personnel were masked to treatment allocation. FIDELIO-DKD and FIGARO-DKD were conducted in accordance with the Declaration of Helsinki. Study protocols were approved by relevant regulatory authorities and ethics committees for each trial site. Written informed consent was obtained from all patients.
2.3. Assessment of PM2.5 exposure
As participant recruitment spanned several years, FIDELITY patients were assigned an antecedent PM2.5 exposure value according to their study site location and year of randomization (annual PM2.5 using an integrated exposure model). This model integrated satellite-based aerosol optical depth measurements, ground-based observations, and chemical transport models to provide accurate estimates of PM2.5 concentrations at a spatial resolution of 1 km × 1 km grids [15,16].
2.4. Outcomes
Outcomes include a composite CV outcome (CV death, nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure), composite kidney outcome (kidney failure, sustained ≥57 % decrease in eGFR from baseline over at least ≥4 weeks, kidney-related death), combined composite CV and kidney outcome, all-cause mortality, and all-cause hospitalization. Additional efficacy outcomes included changes in UACR and eGFR from baseline to month 48. The outcome definitions and endpoint adjudication criteria of the FIDELITY analysis were published previously [13,14]. In summary, blinded adjudication of clinical outcomes was performed by an independent Clinical Event Committee, who were responsible for classifying all death and hospitalization events, and for determining whether prespecified endpoint criteria were met for CV, kidney, or other fatal and nonfatal events.
Safety outcomes were reported as treatment-emergent adverse events (AEs). AEs were considered treatment emergent if they started or worsened during study drug intake or up to 3 days after any treatment interruption [13,14]. Changes over time in blood pressure were also assessed.
2.5. Statistical analysis
All analyses were performed in randomized patients without critical Good Clinical Practice violations. Baseline characteristics and finerenone efficacy included all randomized patients (full analysis set) and finerenone safety was assessed in patients who took ≥1 dose of study drug (safety analysis set).
Analyses were performed in subgroups split by quartiles (Q) of PM2.5 exposure using median and interquartile range as cutoffs (≤Q1, >Q1 and ≤Q2, >Q2 and ≤Q3, >Q3), by median PM2.5 exposure (≤ or > median), and by National Ambient Air Quality Standard (NAAQS) limit (≤ or > 9.0 μg/m3). Efficacy outcomes were also assessed using PM2.5 as a continuous variable.
Overall effects of increasing PM2.5 and treatment effects of finerenone for time-to-event outcomes were expressed as hazard ratio (HR) and 95 % CIs, derived using stratified Cox proportional hazards models. Event probabilities were evaluated for the composite CV and kidney outcomes, components of the composite outcomes, and for mortality and all-cause hospitalization.
Changes over time in UACR and eGFR were analyzed using mixed effects models. Additional information on the study methods can be found in the Supplementary Methods in the Supplementary Material. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).
3. Results
3.1. Patients
In total, 12,990 patients were included in the full analysis set (Fig. S1). The median follow-up of FIDELITY was 3.0 years (interquartile range, 2.3–3.8), and the median PM2.5 exposure was 15.5 µg/m3 (interquartile range, 9.8–21.0), with no difference between finerenone and placebo treatment groups (15.7 [9.8–21.2] vs 15.4 [9.7–20.9] μg/m3, respectively) (Fig. 1 and Fig. S2). Most patients fell within the 5- to 25-µg/m3 PM2.5 value range (Fig. 1), although distribution of patients across PM2.5 quartiles varied by world region (Fig. S2a). Fig. S2b summarizes the global distribution of treatment centers.
Fig. 1.
Distribution of baseline PM2.5 exposure, and the effect of increasing PM2.5 on time to composite CV and kidney outcomes in the FIDELITY population (full analysis set).
(A) Distribution of baseline PM2.5 exposure; (B) Effect of increasing PM2.5 exposure on time to composite CV and kidney outcomes. Events were considered from randomization to end-of-study visit and adjudicated by an independent adjudication committee. A stratified Cox proportional hazards model including treatment and PM2.5 (continuous) was applied. The hazard ratio is related to each 5 µg/m3 increase of baseline PM2.5. All patients were assigned the annual PM2.5 values of their respective centers according to the year of randomization. Abbreviations: CV, cardiovascular; eGFR, estimated glomerular filtration rate; HHF, hospitalization for heart failure; PM2.5, particulate matter with an aerodynamic diameter <2.5 µm; Q, quartile. *CV death, nonfatal myocardial infarction, nonfatal stroke, or HHF. †Kidney failure, sustained ≥57 % decrease in eGFR from baseline over ≥4 weeks, or kidney-related death. ‡CV death, nonfatal myocardial infarction, nonfatal stroke, or HHF; kidney failure, sustained ≥57 % decrease in eGFR from baseline over at least 4 weeks, or kidney-related death.
3.1.1. Baseline characteristics
Patient baseline characteristics were generally balanced between treatment groups (Table 1). However, compared with patients in the lowest quartile (PM2.5 ≤ Q1), patients in the highest quartile (PM2.5 > Q3) were younger (mean age, 66.2 vs 62.4 years) and more likely to be current smokers (12.3 vs 20.3 %), have ∼9-cm smaller waist circumference (111.9 versus 102.4 cm) and be of Asian race (4.6 versus 45.8 %). Additionally, patients in PM2.5 > Q3 were more likely to be from Eastern Europe than patients in PM2.5 ≤ Q1 (34.7 versus 2.3 %) and were less likely to be of White race (49.8 versus 77.0 %) (Fig. S3 and Table 1). Patients in PM2.5 > Q3 were less likely to have history of CVD versus patients in ≤Q1 (42.0 versus 47.2 %) and had lower mean levels of high-sensitivity C-reactive protein (4.5 versus 5.1 mg/L), an indicator for CVD. Furthermore, patients in PM2.5 > Q3 had more advanced CKD (UACR ≥300 mg/g: 73.8 versus 59.4 %), higher median UACR levels (639.64 versus 415.99 mg/g) and nominally higher mean eGFR levels at baseline (61.32 versus 55.22 mL/min/1.73 m2) versus patients in PM2.5 ≤ Q1 (Fig. S4).
Table 1.
Baseline demographic and clinical characteristics by PM2.5 exposure quartiles in patients treated with finerenone or placebo (FAS).
| Characteristic | PM2.5 quartiles |
|||||||
|---|---|---|---|---|---|---|---|---|
| ≤Q1 |
>Q1–≤Q2 |
>Q2–≤Q3 |
>Q3 |
|||||
| Finerenone (n = 630) |
Placebo (n = 1656) |
Finerenone (n = 1595) |
Placebo (n = 1615) |
Finerenone (n = 1624) |
Placebo (n = 1633) |
Finerenone (n = 1649) |
Placebo (n = 1588) |
|
| Age, years, mean (SD) | 66.1 (9.2) | 66.4 (9.6) | 65.5 (9.1) | 65.9 (9.5) | 64.7 (9.1) | 64.8 (9.1) | 62.6 (9.6) | 62.2 (10.0) |
| Sex, male, n (%) | 1151 (70.6) | 1192 (72.0) | 1149 (72.0) | 1195 (74.0) | 1064 (65.5) | 1109 (67.9) | 1099 (66.6) | 1099 (69.2) |
| Race, n (%) | ||||||||
| White | 1251 (76.7) | 1278 (77.2) | 1153 (72.3) | 1127 (69.8) | 1220 (75.1) | 1227 (75.1) | 825 (50.0) | 788 (49.6) |
| Black/African American | 178 (10.9) | 176 (10.6) | 47 (2.9) | 65 (4.0) | 8 (0.5) | 17 (1.0) | 18 (1.1) | 11 (0.7) |
| Asian | 71 (4.4) | 80 (4.8) | 372 (23.3) | 397 (24.6) | 234 (14.4) | 224 (13.7) | 736 (44.6) | 746 (47.0) |
| Other | 130 (8.0) | 122 (7.4) | 23 (1.4) | 26 (1.6) | 162 (10.0) | 165 (10.1) | 70 (4.2) | 43 (2.7) |
| Region n (%) | ||||||||
| Western Europe | 398 (24.4) | 417 (25.2) | 713 (44.7) | 761 (47.1) | 117 (7.2) | 112 (6.9) | 116 (7.0) | 102 (6.4) |
| Eastern Europe | 39 (2.4) | 38 (2.3) | 271 (17.0) | 248 (15.4) | 707 (43.5) | 700 (42.9) | 575 (34.9) | 548 (34.5) |
| North America | 922 (56.6) | 934 (56.4) | 102 (6.4) | 91 (5.6) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| Asia | 30 (1.8) | 32 (1.9) | 349 (21.9) | 364 (22.5) | 420 (25.9) | 407 (24.9) | 782 (47.4) | 786 (49.5) |
| Latin America | 74 (4.5) | 77 (4.6) | 150 (9.4) | 138 (8.5) | 353 (21.7) | 380 (23.3) | 142 (8.6) | 120 (7.6) |
| Other* | 167 (10.2) | 158 (9.5) | 10 (0.6) | 13 (0.8) | 27 (1.7) | 34 (2.1) | 34 (2.1) | 32 (2.0) |
| Systolic blood pressure, mm Hg, mean (SD) | 136.6 (15.1) | 136.1 (14.8) | 137.9 (14.3) | 138.6 (14.4) | 136.9 (14.0) | 137.0 (13.5) | 135.8 (13.2) | 135.2 (14.0) |
| Diastolic blood pressure, mm Hg, mean (SD) | 75.2 (10.2) | 75.5 (10.1) | 76.0 (10.0) | 76.1 (10.0) | 77.0 (9.3) | 76.9 (9.2) | 77.0 (8.9) | 77.0 (9.0) |
| BMI, kg/m2, mean (SD) | 33.2 (6.7) | 33.0 (6.4) | 31.3 (6.0) | 30.9 (5.7) | 31.4 (5.6) | 31.6 (5.8) | 29.5 (5.2) | 29.6 (5.5) |
| Duration of diabetes, years, mean (SD) | 16.6 (9.3) | 16.3 (8.8) | 15.9 (8.8) | 15.7 (8.9) | 15.0 (8.7) | 15.2 (8.7) | 14.3 (8.0) | 14.2 (8.0) |
| HbA1c, %, mean (SD) | 7.7 (1.3) | 7.6 (1.3) | 7.6 (1.3) | 7.6 (1.3) | 7.8 (1.4) | 7.8 (1.4) | 7.7 (1.4) | 7.8 (1.4) |
| Serum potassium, mmol/L, mean (SD) | 4.3 (0.4) | 4.3 (0.4) | 4.4 (0.4) | 4.4 (0.4) | 4.4 (0.5) | 4.4 (0.5) | 4.4 (0.5) | 4.4 (0.5) |
| Waist–hip ratio, mean (SD) | 1.02 (0.13) | 1.02 (0.14) | 1.00 (0.10) | 1.00 (0.10) | 1.00 (0.11) | 1.01 (0.12) | 0.98 (0.1) | 0.98 (0.1) |
| Waist circumference, cm, mean (SD) | 112.0 (16.8) | 111.8 (16.1) | 107.5 (15.1) | 106.7 (15.0) | 106.3 (13.7) | 107.2 (13.7) | 102.2 (13.1) | 102.7 (13.9) |
| hs-CRP, mg/L, mean (SD) | 5.3 (9.3) | 4.9 (8.8) | 4.1 (7.1) | 4.3 (9.5) | 5.2 (12.3) | 5.1 (9.5) | 4.8 (12.1) | 4.2 (8.9) |
| Heart rate, bpm, mean (SD) | 71.8 (12.1) | 71.2 (11.9) | 73.3 (11.7) | 72.8 (11.7) | 72.7 (10.9) | 73.0 (11.0) | 74.9 (10.8) | 75.0 (10.9) |
| eGFR, mL/min/1.73 m2, mean (SD) | 55.1 (21.0) | 55.4 (20.4) | 54.6 (20.2) | 54.6 (20.3) | 59.2 (22.1) | 59.1 (22.1) | 61.0 (22.3) | 61.6 (23.4) |
| eGFR, mL/min/1.73 m2, n (%) | ||||||||
| <25 | 24 (1.5) | 19 (1.1) | 19 (1.2) | 24 (1.5) | 21 (1.3) | 15 (0.9) | 17 (1.0) | 23 (1.4) |
| 25 to <45 | 599 (36.7) | 582 (35.1) | 578 (36.2) | 589 (36.5) | 495 (30.5) | 495 (30.3) | 440 (26.7) | 446 (28.1) |
| 45 to <60 | 432 (26.5) | 463 (28.0) | 457 (28.7) | 453 (28.0) | 402 (24.8) | 422 (25.8) | 420 (25.5) | 377 (23.7) |
| ≥60 | 575 (35.3) | 592 (35.7) | 541 (33.9) | 549 (34.0) | 706 (43.5) | 700 (42.9) | 771 (46.8) | 741 (46.7) |
| UACR, mg/g, median (Q1-Q3) | 411.2 (136.3–975.7) | 418.8 (132.0–1016.3) | 484.5 (187.5–1072.3) | 494.3 (181.8–1079.2) | 567.3 (226.2–1139.3) | 530.6 (210.6–1173.6) | 624.8 (264.6–1343.8) | 653.1 (306.6–1440.0) |
| UACR, mg/g, n (%) | ||||||||
| <30 | 31 (1.9) | 27 (1.6) | 34 (2.1) | 33 (2.0) | 33 (2.0) | 31 (1.9) | 22 (1.3) | 19 (1.2) |
| 30 to <300 | 631 (38.7) | 642 (38.8) | 531 (33.3) | 523 (32.4) | 474 (29.2) | 474 (29.0) | 430 (26.1) | 376 (23.7) |
| ≥300 | 968 (59.4) | 985 (59.5) | 1029 (64.5) | 1059 (65.6) | 1117 (68.8) | 1128 (69.1) | 1196 (72.5) | 1192 (75.1) |
| History of CVD, n (%) | 765 (46.9) | 786 (47.5) | 734 (46.0) | 763 (47.2) | 749 (46.1) | 772 (47.3) | 725 (44.0) | 634 (39.9) |
| Current smoker, n (%) | 194 (11.9) | 210 (12.7) | 282 (17.7) | 252 (15.6) | 254 (15.6) | 234 (14.3) | 329 (20.0) | 327 (20.6) |
| Medication use at baseline,†n (%) | ||||||||
| RASi | 1626 (99.8) | 1655 (>99.9) | 1594 (>99.9) | 1611 (99.8) | 1621 (99.8) | 1629 (99.8) | 1646 (99.8) | 1585 (99.8) |
| Beta blockers | 867 (53.2) | 883 (53.3) | 788 (49.4) | 779 (48.2) | 849 (52.3) | 900 (55.1) | 728 (44.1) | 705 (44.4) |
| Diuretics | 959 (58.8) | 971 (58.6) | 897 (56.2) | 893 (55.3) | 800 (49.3) | 850 (52.1) | 662 (40.1) | 669 (42.1) |
| Loop diuretics | 443 (27.2) | 416 (25.1) | 369 (23.1) | 379 (23.5) | 308 (19.0) | 364 (22.3) | 259 (15.7) | 262 (16.5) |
| Thiade diuretics | 487 (29.9) | 496 (30.0) | 445 (27.9) | 402 (24.9) | 361 (22.2) | 345 (21.1) | 312 (18.9) | 298 (18.8) |
| Statins | 1322 (81.1) | 1364 (82.4) | 1211 (75.9) | 1222 (75.7) | 1119 (68.9) | 1182 (72.4) | 999 (60.6) | 968 (61.0) |
| Potassium supplements | 118 (7.2) | 99 (6.0) | 17 (1.1) | 23 (1.4) | 40 (2.5) | 42 (2.6) | 21 (1.3) | 25 (1.6) |
| Potassium-lowering agents | 6 (0.4) | 11 (0.7) | 42 (2.6) | 34 (2.1) | 17 (1.0) | 16 (1.0) | 29 (1.8) | 27 (1.7) |
| Antidiabetic medication | ||||||||
| Insulins and analogues | 960 (58.9) | 954 (57.6) | 946 (59.3) | 913 (56.5) | 954 (58.7) | 935 (57.3) | 998 (60.5) | 960 (60.5) |
| DPP-4 inhibitors | 359 (22.0) | 389 (23.5) | 520 (32.6) | 517 (32.0) | 386 (23.8) | 388 (23.8) | 381 (23.1) | 315 (19.8) |
| GLP-1RAs | 195 (12.0) | 169 (10.2) | 158 (9.9) | 144 (8.9) | 87 (5.4) | 81 (5.0) | 57 (3.5) | 52 (3.3) |
| SGLT-2 inhibitors | 131 (8.0) | 151 (9.1) | 141 (8.8) | 128 (7.9) | 96 (5.9) | 107 (6.6) | 68 (4.1) | 51 (3.2) |
| Metformin | 956 (58.7) | 960 (58.0) | 917 (57.5) | 875 (54.2) | 1000 (61.6) | 973 (59.6) | 928 (56.3) | 930 (58.6) |
| Sulfonamides | 406 (24.9) | 443 (26.8) | 426 (26.7) | 421 (26.1) | 420 (25.9) | 417 (25.5) | 434 (26.3) | 411 (25.9) |
| Alpha glucosidase inhibitors | 24 (1.5) | 22 (1.3) | 71 (4.5) | 72 (4.5) | 39 (2.4) | 54 (3.3) | 188 (11.4) | 182 (11.5) |
| Meglitinides | 27 (1.7) | 20 (1.2) | 76 (4.8) | 77 (4.8) | 80 (4.9) | 89 (5.5) | 89 (5.4) | 71 (4.5) |
| Thiazolidinediones | 56 (3.4) | 50 (3.0) | 76 (4.8) | 75 (4.6) | 56 (3.4) | 45 (2.8) | 79 (4.8) | 78 (4.9) |
Abbreviations: BMI, body mass index; CVD, cardiovascular disease; DPP-4, dipeptidyl peptidase-4; eGFR, estimated glomerular filtration rate; FAS, full analysis set; GLP-1RA, glucagon-like peptide-1 receptor agonist; HbA1c, glycated hemoglobin; hs-CRP, high-sensitivity C-reactive protein; PM2.5, particulate matter with an aerodynamic diameter <2.5 µm; Q, quartile; RASi, renin–angiotensin system inhibitor; SGLT-2, sodium-glucose co-transporter-2; UACR, urine albumin-to-creatinine ratio.
Other includes American Indian or Alaska Native, Native Hawaiian or other Pacific Islander, not reported, and multiple categories.
Multiple drug groups per drug are possible. Therefore, the same drug may be counted in >1 category for the same patient.
Patient demographics were conducted on the FAS, which included all 12,990 randomized patients.
Quartile cutoffs: Q1 (9.80) = lowest; Q2 (15.50) = median; Q3 (21.00) = highest.
3.2. Efficacy
3.2.1. CV outcomes
PM2.5 exposure was associated with an increased risk of the composite CV outcome (P = 0.0287) (Fig. 1b). The composite CV outcome occurred in 823/6498 patients (12.7 %) randomized to finerenone and 938/6492 patients (14.4 %) randomized to placebo (HR, 0.86; 95 % CI, 0.78–0.95) (Fig. 2a). Finerenone was associated with improved composite CV outcomes across strata of PM2.5 exposure (Pinteraction = 0.37 for PM2.5 quartiles, 0.96 for PM2.5 median subgroups). When the individual components of the composite CV outcome were considered, there was a trend for interaction of PM2.5 with the finerenone effect in the mid-to-high quartile of PM2.5 (>Q2–≤Q3) (Pinteraction = 0.052 for nonfatal MI) (Fig. S5). Increasing PM2.5 exposure, analyzed as a continuous variable, was associated with higher probability of CV events over 3.5 years in both treatment groups (Fig. 3a). The numbers needed to treat (NNTs) to prevent one CV event over 3.5 years were 50 and 65 in the ≤ and > median PM2.5 exposure subgroup, respectively.
Fig. 2.
Effect of finerenone versus placebo on time to composite CV and kidney outcomes by PM2.5 subgroup (full analysis set).
(A) Composite CV outcome*; (B) composite kidney outcome†; (C) combined composite CV and kidney outcomes.‡ Events were considered from randomization to end-of-study visit and adjudicated by an independent adjudication committee. A stratified Cox proportional hazards model including treatment was calculated separately by subgroup category. Interaction P values are based on a stratified Cox proportional hazards model including treatment, subgroup, and treatment-by-subgroup interaction. PM2.5 is provided by patient treatment center. Quartile cutoffs: Q1 (9.80) = lowest; Q2 (15.50) = median; Q3 (21.00) = highest. Abbreviations: CV, cardiovascular; eGFR, estimated glomerular filtration rate; HHF, hospitalization for heart failure; PM2.5, particulate matter with an aerodynamic diameter <2.5 µm; PY, patient-years; Q, quartile. *CV death, nonfatal myocardial infarction, nonfatal stroke, or HHF. †Kidney failure, sustained ≥57 % decrease in eGFR from baseline over ≥4 weeks, or kidney-related death. ‡CV death, nonfatal myocardial infarction, nonfatal stroke, or HHF; kidney failure, sustained ≥57 % decrease in eGFR from baseline over at least 4 weeks, or kidney-related death.
Fig. 3.
Effect of finerenone versus placebo on predicted probability of a composite CV and/or composite kidney event at 3.5 years by continuous PM2.5 (full analysis set).
(A) Composite CV outcome*; (B) composite kidney outcome†; (C) combined composite CV and kidney outcomes.‡ Cox proportional hazards model fitted with covariates treatment, PM2.5, study, region, albuminuria and eGFR at screening, and CV disease history. Splines used knots at 1st, 50th, and 99th percentiles of PM2.5 value. Values of PM2.5 were truncated between the 5th and 95th percentiles. PM2.5 value provided by patient treatment center. Abbreviations: CV, cardiovascular; eGFR, estimated glomerular filtration rate; HHF, hospitalization for heart failure; PM2.5, particulate matter with an aerodynamic diameter <2.5 µm. *CV death, nonfatal myocardial infarction, nonfatal stroke, or HHF. †Kidney failure, sustained ≥57 % decrease in eGFR from baseline over at least 4 weeks, or kidney-related death. ‡CV death, nonfatal myocardial infarction, nonfatal stroke, or HHF; kidney failure, sustained ≥57 % decrease in eGFR from baseline over at least 4 weeks, or kidney-related death.
3.2.2. Kidney outcomes
PM2.5 exposure was associated with an increased risk of the composite kidney outcome (P < 0.0001) (Fig. 1b). Finerenone was associated with reduced risk of kidney events across the strata of PM2.5 exposure (Pinteraction = 0.14 for PM2.5 quartiles, 0.08 for PM2.5 median subgroups). The composite kidney outcome occurred in 356/6498 patients (5.5 %) randomized to finerenone and 465/6492 patients (7.2 %) randomized to placebo (HR, 0.76; 95 % CI, 0.66–0.88) (Fig. 2b). A trend was observed for a greater effect of finerenone when PM2.5 values were above the median (Pinteraction = 0.0753). When the individual components of the composite kidney outcome were considered, there was trend for interaction of PM2.5 with the finerenone effect when PM2.5 values were above the median for onset of kidney failure (Pinteraction = 0.059) (Fig. S6). Only one event was recorded for kidney-related death (HR estimation was not possible due to insufficient events). When considered as a continuous variable, increasing PM2.5 exposure was associated with higher probability of kidney events over 3.5 years in both treatment groups (Fig. 3b). The NNTs to prevent one kidney event over 3.5 years were 123 and 39 in the ≤ and > median PM2.5 exposure subgroup, respectively.
3.2.3. Combined composite CV and kidney outcomes
PM2.5 exposure was also associated with an increased risk for the combined composite CV and kidney outcome (P = 0.0131) (Fig. 1b). Consistent findings were observed for the combined composite CV/kidney outcome, which occurred in 1086/6498 patients (16.7 %) randomized to finerenone and 1290/6492 patients (19.9 %) randomized to placebo (HR, 0.83; 95 % CI, 0.76–0.90) (Fig. 2c). Finerenone had a similar beneficial impact on the combined composite CV/kidney outcome across strata of PM2.5 exposure (Pinteraction = 0.74 for quartiles, 0.52 for median subgroups), and the NNTs to prevent one composite CV/kidney event over 3.5 years were 34 and 29 for the ≤ and > median PM2.5 exposure subgroup, respectively. Increasing PM2.5 exposure was associated with higher probabilities of combined composite CV/kidney outcome events over 3.5 years in both treatment groups when considered as a continuous variable (Fig. 3c).
3.2.4. Mortality and hospitalization
Significant heterogeneity in all-cause mortality was detected between PM2.5 quartiles (Pinteraction = 0.04), with a more pronounced effect for finerenone versus placebo in mid-PM2.5 quartiles (>Q1–≤Q2, HR, 0.75; 95 % CI, 0.59–0.96; >Q2–≤Q3, HR, 0.76; 95 % CI, 0.61–0.95), but no heterogeneity was seen when comparing the median subgroups (Pinteraction = 0.70) (Fig. S7a). A similar numerical trend was shown for all-cause hospitalization across quartiles of PM2.5 exposure (Pinteraction = 0.14) and median subgroups (Pinteraction = 0.66) (Fig. S7b). Patients at either end of the PM2.5 exposure range had higher risk of all-cause mortality and all-cause hospitalization (Fig. S7c and d).
3.2.5. Change in UACR from baseline over time
In patients exposed to PM2.5 levels ≤9.0 μg/m3 (the NAAQS limit), finerenone reduced UACR by 36 % at month 4 versus placebo (least-squares mean [LSM] treatment ratio, 0.64; 95 % CI, 0.60–0.68; P < 0.0001) (Fig. 4a). In patients with PM2.5 exposure >9.0 μg/m3, finerenone reduced UACR by 31 % at month 4 versus placebo (LSM treatment ratio, 0.69; 95 % CI, 0.66–0.72; P < 0.0001) (Fig. 4b). Finerenone resulted in similar improvements in UACR across quartiles, with reductions of 36 %, 30 %, 31 %, and 31 % versus placebo in ≤Q1, >Q1–≤Q2, >Q2–≤Q3, and >Q3, respectively (P < 0.0001 for all), and this effect was maintained through month 48 (Fig. S8).
Fig. 4.
Change in UACR and eGFR over time by NAAQS cutoffs* in patients treated with finerenone or placebo (full analysis set).
(A) UACR change at PM2.5 exposure ≤9 µg/m3; (B) UACR change at PM2.5 exposure >9 µg/m3; (C) eGFR change at PM2.5 exposure ≤9 µg/m3; (D) eGFR change at PM2.5 exposure >9 µg/m3. Abbreviations: eGFR, estimated glomerular filtration rate; EOS, end of study; LS, least-squares; NAAQS, National Ambient Air Quality Standard; PM2.5, particulate matter with an aerodynamic diameter <2.5 µm; Q, quartile; UACR, urine albumin-to-creatinine ratio. *Based on the NAAQS for the annual mean PM2.5 exposure limit in the United States of 9.0 µg/m3. Quartile cutoffs: Q1 (9.80) = lowest; Q2 (15.50) = median; Q3 (21.00) = highest.
3.2.6. eGFR decline
An initial decrease in eGFR from baseline to month 1 was observed with finerenone versus placebo across all PM2.5 strata, but finerenone significantly attenuated the eGFR decline from month 4 to the end-of-study visit (chronic eGFR slope) (Fig. 4c and d). In patients exposed to PM2.5 levels ≤9.0 μg/m3 (NAAQS limit), the change in total eGFR slope from baseline to month 44 was −2.75 for finerenone and −3.45 for placebo (LSM difference, 0.70; 95 % CI, 0.38–1.01; P < 0.0001) (Fig. 4c). The changes for those exposed to PM2.5 > 9.0 μg/m3 were −3.39 for finerenone and −3.79 for placebo (LSM difference, 0.40; 95 % CI, 0.22–0.58; P < 0.0001) (Fig. 4d). Overall, CKD progression was slower with finerenone versus placebo, independent of PM2.5 quartile (Fig. S9).
3.3. Safety outcomes
Finerenone safety findings were generally similar between treatment groups and comparable across PM2.5 quartiles (Table 2). Overall, AE rates leading to discontinuation were low across PM2.5 exposure quartiles and well balanced between treatment groups. Fewer serious AEs occurred in patients treated with finerenone versus placebo, irrespective of PM2.5 exposure. The incidence of investigator-reported hyperkalemia was more frequent in patients treated with finerenone versus placebo across all PM2.5 quartiles (Table 2). Incidence of serious hyperkalemia leading to hospitalization with finerenone and placebo was low, irrespective of PM2.5 quartiles.
Table 2.
Treatment-emergent AEs by PM2.5 quartiles in patients treated with finerenone or placebo (safety analysis set).
| n (%) | PM2.5 quartiles |
|||||||
|---|---|---|---|---|---|---|---|---|
| ≤Q1 |
>Q1-≤Q2 |
>Q2-≤Q3 |
>Q3 |
|||||
| Finerenone (n = 1627) | Placebo (n = 1653) |
Finerenone (n = 1592) |
Placebo (n = 1609) |
Finerenone (n = 1623) |
Placebo (n = 1627) |
Finerenone (n = 1647) |
Placebo (n = 1585) |
|
| Any AE | 1433 (88.1) | 1450 (87.7) | 1448 (91.0) | 1463 (90.9) | 1338 (82.4) | 1351 (83.0) | 1363 (82.8) | 1328 (83.8) |
| Related to study drug | 332 (20.4) | 236 (14.3) | 333 (20.9) | 242 (15.0) | 254 (15.7) | 169 (10.4) | 285 (17.3) | 212 (13.4) |
| Leading to discontinuation of study drug | 134 (8.2) | 98 (5.9) | 116 (7.3) | 111 (6.9) | 79 (4.9) | 69 (4.2) | 85 (5.2) | 72 (4.5) |
| Any SAE | 552 (33.9) | 568 (34.4) | 503 (31.6) | 562 (34.9) | 457 (28.2) | 514 (31.6) | 542 (32.9) | 537 (33.9) |
| Related to study drug | 33 (2.0) | 22 (1.3) | 20 (1.3) | 11 (0.7) | 12 (0.7) | 11 (0.7) | 18 (1.1) | 17 (1.1) |
| Leading to discontinuation of study drug | 50 (3.1) | 38 (2.3) | 34 (2.1) | 56 (3.5) | 28 (1.7) | 33 (2.0) | 33 (2.0) | 27 (1.7) |
| Death | 23 (1.4) | 26 (1.6) | 20 (1.3) | 49 (3.0) | 30 (1.8) | 44 (2.7) | 36 (2.2) | 32 (2.0) |
| Any TE hyperkalemia | 242 (14.9) | 83 (5.0) | 222 (13.9) | 102 (6.3) | 182 (11.2) | 94 (5.8) | 262 (15.9) | 169 (10.7) |
| Related to study drug | 143 (8.8) | 47 (2.8) | 144 (9.0) | 56 (3.5) | 121 (7.5) | 50 (3.1) | 163 (9.9) | 96 (6.1) |
| Leading to permanent discontinuation of study drug | 44 (2.7) | 11 (0.7) | 26 (1.6) | 9 (0.6) | 19 (1.2) | 8 (0.5) | 21 (1.3) | 10 (0.6) |
| Serious TE hyperkalemia | 30 (1.8) | 9 (0.5) | 14 (0.9) | 2 (0.1) | 9 (0.6) | 3 (0.2) | 16 (1.0) | 2 (0.1) |
| Related to study drug | 16 (1.0) | 4 (0.2) | 10 (0.6) | 0 (0) | 6 (0.4) | 2 (0.1) | 11 (0.7) | 2 (0.1) |
| Leading to permanent discontinuation of study drug | 7 (0.4) | 0 (0) | 1 (<0.1) | 0 (0) | 1 (<0.1) | 0 (0) | 1 (<0.1) | 2 (0.1) |
| Leading to hospitalization | 26 (1.6) | 6 (0.4) | 13 (0.8) | 1 (<0.1) | 8 (0.5) | 3 (0.2) | 14 (0.9) | 0 (0) |
| Life-threatening | 3 (0.2) | 3 (0.2) | 1 (<0.1) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 2 (0.1) |
| Fatal | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
For TE events, all interruptions were excluded from the person-time at risk; ie, for patients with an interruption, events in the period from interruption start +3 days until end of interruption were not considered. PM2.5 is provided by patient treatment center. Quartile cutoffs: Q1 (9.80) = lowest; Q2 (15.50) = median; Q3 (21.00) = highest. Safety outcomes were conducted on the safety analysis set, which included 12 963 randomized patients.
Abbreviations: AE, adverse event; PM2.5, particulate matter with an aerodynamic diameter <2.5 µm; Q, quartile; SAE, serious adverse event; TE, treatment-emergent.
3.3.1. Blood pressure
Blood pressure control over time, as indicated by mean systolic blood pressure (SBP), was comparable across PM2.5 quartiles in both treatment groups (Fig. S10). Finerenone was associated with reduced SBP versus placebo regardless of PM2.5. For patients with lower PM2.5 exposure, mean reduction from baseline to month 4 was approximately 4 mm Hg versus placebo (≤Q1, −3.6 [standard deviation (SD), 15.8] versus 0.5 [SD, 15.1] mm Hg). For patients in >Q3, the reduction was approximately 3 mm Hg versus placebo (−2.8 [SD, 14.7] versus 0.4 [SD, 14.0] mm Hg). A similar reduction from baseline to month 4 was observed with finerenone versus placebo in the mid-PM2.5 quartiles (>Q1–≤Q2, −3.6 [SD, 15.4] mm Hg versus 0.5 [SD, 15.4]; >Q2–≤Q3, −2.9 [SD, 14.4] mm Hg versus 0.4 [SD, 14.0]).
4. Discussion
In this post hoc analysis of FIDELITY, higher PM2.5 air pollution exposure levels were associated with increased risks of CV and kidney outcomes in patients with CKD and T2D. The beneficial effects of finerenone versus placebo in reducing primary composite CV and kidney outcomes were consistent across PM2.5 exposure quartiles. Although relative risk reductions with finerenone were mostly similar regardless of ambient PM2.5, absolute risk reductions were numerically greater in patients exposed to higher PM2.5 levels. The NNTs were lower among patients exposed to higher versus lower PM2.5 levels for kidney outcomes and most CV outcomes.
Air pollution exposure is linked to cardiometabolic risk, CV events including mortality, and incidence and progression of CKD and T2D [7,17,18]. Even after adjusting for prognostic factors including the use of renin–angiotensin system blockers and glycemic control, higher PM2.5 exposure was independently associated with increased risk of progression to end-stage kidney disease in patients with CKD and diabetes [17]. Patients with T2D are more likely to succumb to the adverse health effects of PM2.5, which may further amplify pollution-related CV risk [19]. Several studies exploring associations between PM2.5 and diabetes-related mortality have found increased risk of 18 % to 49 % for every 10-μg/m3 increase in PM2.5 [20]. These risks persist well below the current NAAQS limit [21]. Consistent with increased risk of T2D and preexisting CV or CKD, absolute risk reduction with finerenone and NNTs to prevent CV or CKD events were more favorable in patients with higher PM2.5 exposure. Some evidence suggests PM2.5 exposure may represent an important surrogate for CV-related risk [22], possibly highlighting populations who could potentially benefit from cardiometabolic therapies.
A post hoc analysis of Systolic Blood Pressure Intervention Trial (SPRINT) found that patients living in areas with the high PM2.5 exposure derived greater benefits from intensive blood pressure treatment (target SBP <120 mm Hg) than patients residing in cleaner locations, suggesting heightened susceptibility of these individuals to CV events and an association between air pollution exposure and hypertension [23]. No interaction between PM2.5 and blood pressure control in either treatment group in the SPRINT analysis was found. Nevertheless, results from SPRINT highlight the need for integrated public health strategies that address both air pollution control and effective mitigation of CV risks [10,11,23]. Additionally, integrating environmental exposure data together with other social determinants could help guide personalized treatment approaches and optimize outcomes for patients with high-risk CKD and T2D [24].
Patients exposed to the highest PM2.5 levels in FIDELITY were predominantly from low- to middle-income countries of Asia and Eastern Europe and differ substantially in their baseline cardiometabolic risk. These areas are experiencing growing rates of CKD and T2D [25]. This geographic juxtaposition between high PM2.5 exposure and higher rates of CKD and T2D may not be coincidental: recent studies suggest a causative role for PM2.5 [7], and a Global Burden of Disease study estimated that one fifth of the worldwide T2D burden is attributable to chronic PM2.5 exposure [26].
In our analysis, individuals in PM2.5 > Q3 had more advanced CKD, higher median UACR levels, and nominally higher mean eGFR levels at baseline versus patients in ≤Q1. In a cohort study of >2.4 million US veterans with a median of 8.5 years of follow-up, a 10-µg/m3 PM2.5 increase was associated with increased odds of developing T2D and CKD [27]. T2D mediated a proportion of the association between PM2.5 and a number of kidney events including incident eGFR <60 mL/min/1.73 m2 (4.7 %), incident CKD (4.8 %), ≥30 % eGFR decline (5.8 %), and end-stage kidney disease or ≥50 % eGFR decline (17.0 %). However, other studies have reported varying results when assessing associations between increased PM2.5 and UACR [28]. Here, finerenone led to significantly greater reductions in UACR from baseline to month 4 versus placebo irrespective of PM2.5 subgroup.
The mechanisms by which PM2.5 confers cardiometabolic risk have been discussed extensively elsewhere [2,5]. Most mechanisms are common to CVD and include endothelial dysfunction, autonomic dysregulation, inflammation, oxidative stress, and profibrotic pathways. Thus, PM2.5 may amplify effects of other risk factors, which may be addressed by treatment with finerenone, known to ameliorate endothelial dysfunction, oxidative stress, inflammation, and fibrosis [[29], [30], [31], [32], [33], [34], [35], [36], [37]]. In a rat model of CV and kidney injury, treatment with finerenone improved cardiac and kidney hypertrophy and reduced sodium retention, proteinuria, and several inflammatory and fibrosis-associated biomarkers [38]. Moreover, results from a post hoc proteomic analysis of the FIGARO-DKD trial also showed a reduction in the fibrosis biomarkers fibronectin and osteopontin, and a reduction in the pro-inflammatory adipokine angiopoietin-like protein 2 [39]. These findings suggest finerenone could potentially modify PM2.5-induced CV and kidney events mechanistically through its anti-inflammatory and anti-fibrotic effects.
This analysis has several limitations. Although high-resolution (1 km × 1 km) blended approaches were used to derive PM2.5 exposure, the assignments of exposure values were based on study site rather than individual residences, which may have led to exposure misclassification. This approach might have attenuated the apparent health effects of air pollution, rather than the finding of continued robust estimates shown here. Additionally, our analysis did not control for other exposures, which are well known to associate with high levels of air pollution in many environments [[40], [41], [42]]. Social determinants such as education and socioeconomic status co-segregate with PM2.5 and may have contributed to our observations. Air pollution exposures are known to disproportionately affect minority and socioeconomically disadvantaged populations, making it challenging to separate these effects [[42], [43], [44]]. Furthermore, there was a constraint within the statistical analysis on the probability of event data for the CV and kidney outcomes. Predicted event probabilities were generated across the observed PM2.5 range using 0.1-µg/m³ increments to produce smooth exposure–response curves. Because most PM2.5 values were between 9.8 and 21.0 µg/m³, estimates were most stable in this interval and were consistent with quartile-based forest plots. Confidence intervals widened above 21 µg/m³ due to fewer participants/events at higher exposures.
In the face of increasing environmental health threats within a rapidly changing global environment, advancing our understanding of the complex interplay among environmental PM2.5 exposure, CV and kidney health, access to new therapies, and treatment responses is crucial. Future studies are warranted to validate the value of incorporating PM2.5 exposure into risk prediction and treatment algorithms and ensure availability of high-quality exposure data. Ultimately, evidence-based treatments, coupled with policy-driven regulations to improve air quality, may help reduce the burden attributable to CV and kidney disease.
In this FIDELITY post hoc analysis, PM2.5 exposure influenced risk of CV and kidney outcomes. Finerenone lowered this risk and demonstrated manageable safety irrespective of PM2.5 exposure level. These findings have important implications from both a clinical and air pollution regulatory perspective.
Sources of funding
Funding/Support: This work was supported by Bayer AG, which funded the FIDELIO-DKD and FIGARO-DKD studies and combined analysis.
Disclosures
S. Al-Kindi has nothing to disclose.
Z. Chen has nothing to disclose.
J.-E. Dazard has nothing to disclose.
Y.M.K. Farag was a full-time employee at Bayer U.S. LLC at the time of data analysis. He is now a full-time employee of Alexion AstraZeneca Rare Disease Unit.
G. Filippatos reports lecture fees and/or that he is a committee member of trials and registries sponsored by Amgen, Bayer, Boehringer Ingelheim, Medtronic, Novartis, Servier, and Vifor Pharma. He is a senior consulting editor for JACC Heart Failure and has received research support from the European Union.
P. Rossing reports personal fees from Bayer during the conduct of the study. He has received research support and personal fees from AstraZeneca, Bayer, and Novo Nordisk, and personal fees from Astellas Pharma, Abbott, Boehringer Ingelheim, Eli Lilly, Gilead, Mundipharma, Novartis, Sanofi, and Vifor Pharma; all fees are given to Steno Diabetes Center Copenhagen.
K. Rohwedder is a full-time employee of Bayer AG.
P.R.V. de Oliveira Salerno has nothing to disclose.
C. Scott is a full-time employee of Bayer Corporation.
Z. Zheng is employed by Bayer U.S. LLC.
S. Rajagopalan reports consultancy and scientific advisory board participation with Bayer and Novo Nordisk.
CRediT authorship contribution statement
Sadeer Al-Kindi: Writing – review & editing, Writing – original draft, Methodology, Conceptualization. Zhuo Chen: Writing – review & editing. Jean-Eudes Dazard: Writing – review & editing. Youssef M.K. Farag: Writing – review & editing. Gerasimos Filippatos: Writing – review & editing. Peter Rossing: Writing – review & editing. Katja Rohwedder: Writing – review & editing. Pedro Rafael Vieira de Oliveira Salerno: Writing – review & editing. Charlie Scott: Writing – review & editing, Formal analysis, Data curation. Zihe Zheng: Writing – review & editing, Formal analysis, Data curation. Sanjay Rajagopalan: Writing – review & editing, Writing – original draft, Methodology, Conceptualization.
Declaration of competing interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
Youssef Farag was a full-time employee at Bayer U.S. LLC at the time of data analysis and reports a relationship with Alexion AstraZeneca that includes employment. Gerasimos Filippatos reports relationships with Amgen Inc., Bayer, Boehringer Ingelheim, Medtronic, Novartis, Servier, and Vifor Pharma, that include speaking and lecture fees. Gerasimos Filippatos also reports a relationship with European Union that includes funding grants, and he is a senior consulting editor for JACC Heart Failure. Peter Rossing reports financial support provided by Bayer. Peter Rossing also reports relationships with Abbott, Astellas Pharma, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Gilead, Mundipharma, Novartis, Novo Nordisk, Sanofi, and Vifor Pharma that include funding grants. Katja Rohwedder, Charlie Scott and Zihe Zheng report a relationship with Bayer that includes employment. Sanjay Rajagopalan reports relationships with Bayer and Novo Nordisk that include consulting or advisory.
If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The Executive Committee, in collaboration with the study sponsor, designed the trials and protocols and supervised the trial conduct. In both trials, patient safety was overseen by an independent data monitoring committee. Analyses were conducted by the sponsor; all authors had access to and participated in the interpretation of the data. The study sponsor collected and analyzed the data, and all authors contributed to interpretation of the data; preparation, review, and approval of the manuscript; and the decision to submit the manuscript for publication. Full study investigator lists are available in the supplementary appendices of the FIDELIO-DKD and FIGARO-DKD primary publications (available at: https://www.nejm.org/doi/full/10.1056/NEJMoa2025845 and https://www.nejm.org/doi/full/10.1056/NEJMoa2110956, respectively) [13,14]. Medical writing and editorial support were provided by Aoife Tracey, PhD, and Alison McTavish, MSc (HCG), with funding from Bayer AG. Finally, our esteemed steering committee member, George Bakris, passed away in June 2024 and will be remembered for his passion for science and patient care.
Footnotes
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.ajpc.2026.101670.
Appendix. Supplementary materials
Supplementary Material.
Supplementary Methods
Supplementary Figs. S1–10
References
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